code: def _get_slice_plot(info: _SlicePlotInfo) -> "Axes":
      if len(info.subplots) == 0:
          _, ax = plt.subplots()
          return ax
  
      # Set up the graph style.
      cmap = plt.get_cmap("Blues")
      padding_ratio = 0.05
      plt.style.use(
          "ggplot"
      )  # Use ggplot style sheet for similar outputs to plotly.
  
      if len(info.subplots) == 1:
          # Set up the graph style.
          fig, axs = plt.subplots()
          axs.set_title("Slice Plot")
  
          # Draw a scatter plot.
          sc = _generate_slice_subplot(
              info.subplots[0],
              axs,
              cmap,
              padding_ratio,
              info.target_name,
          )
      else:
          # Set up the graph style.
          min_figwidth = matplotlib.rcParams["figure.figsize"][0] / 2
          fighight = matplotlib.rcParams["figure.figsize"][1]
          # Ensure that each subplot has a minimum width without relying on auto-sizing.
          fig, axs = plt.subplots(
              1,
              len(info.subplots),
              sharey=True,
              figsize=(min_figwidth * len(info.subplots), fighight),
          )
          fig.suptitle("Slice Plot")
  
          # Draw scatter plots.
          for i, subplot in enumerate(info.subplots):
              ax = axs[i]
              sc = _generate_slice_subplot(
                  subplot, ax, cmap, padding_ratio, info.target_name
              )
  
      axcb = fig.colorbar(sc, ax=axs)
      axcb.set_label("Trial")
  
      return axs
  
file_path: optuna/optuna/visualization/matplotlib/_slice.py
imports: from __future__ import annotations
  from collections import defaultdict
  import math
  from typing import Any
  from typing import Callable
  from optuna._experimental import experimental_func
  from optuna.study import Study
  from optuna.trial import FrozenTrial
  from optuna.visualization._slice import _get_slice_plot_info
  from optuna.visualization._slice import _PlotValues
  from optuna.visualization._slice import _SlicePlotInfo
  from optuna.visualization._slice import _SliceSubplotInfo
  from optuna.visualization.matplotlib._matplotlib_imports import _imports
label_desc: Use image node_id 2 for calling a global function with example usage: _get_slice_plot(info) and returns: axs, ax